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			<h1>FORECAST.ETS Function</h1>
			<p>The <b>FORECAST.ETS</b> function is one of the <a href="../UsageInstructions/InsertFunction.htm#statistical" onclick="onhyperlinkclick(this)">statistical functions</a>. It is used to calculate or predict a future value based on existing (historical) values by using the AAA version of the Exponential Smoothing (ETS) algorithm.</p>
			<h3>Syntax</h3> 
			<p><b><em>FORECAST.ETS(target_date, values, timeline, [seasonality], [data_completion], [aggregation])</em></b></p> 
			<p>The <b>FORECAST.ETS</b> function has the following arguments:</p>
			<table style="width: 40%">
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                    <th style="background-color: #f4f4f4" width="150ch"><b>Argument</b></th>
                    <th style="background-color: #f4f4f4"><b>Description</b></th>
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                <tr>
                    <td><b><em>target_date</em></b></td>
                    <td>A date for which you want to predict a new value. Must be after the last date in the <b><em>timeline</em></b>.</td>
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				<tr>
                    <td><b><em>values</em></b></td>
                    <td>A range of the historical values for which you want to predict a new point.</td>
                </tr>
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                    <td><b><em>timeline</em></b></td>
                    <td>A range of date/time values that correspond to the historical values. The <b><em>timeline</em></b> range must be of the same size as the <b><em>values</em></b> range. Date/time values must have a constant step between them (although up to 30% of missing values can be processed as specified by the <b><em>data_completion</em></b> argument and duplicate values can be aggregated as specified by the <b><em>aggregation</em></b> argument).</td>
                </tr>
                <tr>
                    <td><b><em>seasonality</em></b></td>
                    <td>A numeric value that specifies which method should be used to detect the seasonality. It is an optional argument. The possible values are listed in the table below.</td>
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                    <td><b><em>data_completion</em></b></td>
                    <td>A numeric value that specifies how to process the missing data points in the <b><em>timeline</em></b> data range. It is an optional argument. The possible values are listed in the table below.</td>
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                    <td><b><em>aggregation</em></b></td>
                    <td>A numeric value that specifies which function should be used to aggregate identical time values in the <b><em>timeline</em></b> data range. It is an optional argument. The possible values are listed in the table belows.</td>
                </tr>
            </table>
            <p>The <b><em>seasonality</em></b> argument can be one of the following:</p>
            <table style="width: 40%">
                <tr>
                    <th style="background-color: #f4f4f4"><b>Numeric value</b></th>
                    <th style="background-color: #f4f4f4"><b>Behavior</b></th>
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                <tr>
                    <td><b><em>1 or omitted</em></b></td>
                    <td>Seasonality is detected automatically. Positive, whole numbers are used for the length of the seasonal pattern.</td>
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                <tr>
                    <td><b><em>0</em></b></td>
                    <td>No seasonality, the prediction will be linear.</td>
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                <tr>
                    <td><b><em>an integer greater than or equal to 2</em></b></td>
                    <td>The specified number is used for the length of the seasonal pattern.</td>
                </tr>
            </table>
            <p>The <b><em>data_completion</em></b> argument can be one of the following:</p>   
            <table style="width: 40%">
                <tr>
                    <th style="background-color: #f4f4f4"><b>Numeric value</b></th>
                    <th style="background-color: #f4f4f4"><b>Behavior</b></th>
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                <tr>
                    <td><b><em>1 or omitted</em></b></td>
                    <td>Missing points are calculated as the average of the neighbouring points.</td>
                </tr>
                <tr>
                    <td><b><em>0</em></b></td>
                    <td>Missing points are treated as zero values.</td>
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            </table>
            <p>The <b><em>aggregation</em></b> argument can be one of the following:</p>    
            <table style="width: 40%">
                <tr>
                    <th style="background-color: #f4f4f4"><b>Numeric value</b></th>
                    <th style="background-color: #f4f4f4"><b>Function</b></th>
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                <tr>
                    <td><b><em>1 or omitted</em></b></td>
                    <td><a href="../Functions/average.htm" onclick="onhyperlinkclick(this)">AVERAGE</a></td>
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                    <td><b><em>2</em></b></td>
                    <td><a href="../Functions/count.htm" onclick="onhyperlinkclick(this)">COUNT</a></td>
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                    <td><b><em>3</em></b></td>
                    <td><a href="../Functions/counta.htm" onclick="onhyperlinkclick(this)">COUNTA</a></td>
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                    <td><b><em>4</em></b></td>
                    <td><a href="../Functions/max.htm" onclick="onhyperlinkclick(this)">MAX</a></td>
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                    <td><b><em>5</em></b></td>
                    <td><a href="../Functions/median.htm" onclick="onhyperlinkclick(this)">MEDIAN</a></td>
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                    <td><b><em>6</em></b></td>
                    <td><a href="../Functions/min.htm" onclick="onhyperlinkclick(this)">MIN</a></td>
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                    <td><b><em>7</em></b></td>
                    <td><a href="../Functions/sum.htm" onclick="onhyperlinkclick(this)">SUM</a></td>
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            </table> 
            <h3>Notes</h3>
			<p><a href="../UsageInstructions/InsertFunction.htm#applyfunction" onclick="onhyperlinkclick(this)">How to apply</a> the <b>FORECAST.ETS</b> function.</p>
			
			<h3>Examples</h3>
            <p>The figure below displays the result returned by the <b>FORECAST.ETS</b> function.</p>
			<p><img alt="FORECAST.ETS Function" src="../images/forecast-ets.png" /></p>
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